The postgraduate study programme aims at preparing top scientific and research specialists in various areas of mathematics with applications in electrical engineering fields of study, especially in the area of stochastic processes, design of optimization and statistic methods for description of the systems studied, analysis of systems and multisystems using discrete and functional equations, digital topology application, AI mathematical background, transformation and representation of multistructures modelling automated processes, fuzzy preference structures application, multicriterial optimization, research into automata and multiautomata seen in the framework of discrete systems, stability and system controllability. The study programme will also focus on developing theoretical background of the above mentioned areas of mathematics.

Key learning outcomes

The graduates of the postgraduate study programme Mathematics in Electrical Engineering will be prepared for future employment in the area of applied research and in technology research teams. Due to the comprehensive use of computer engineering throughout the study programme, the graduates will be well prepared for work in the area of scientific and technology software development and maintenance. The graduates will also be prepared for management and analytical positions in companies requiring good knowledge of mathematical modelling, statistics and optimization.

Occupational profiles of graduates with examples

The graduates of the postgraduate study programme Mathematics in Electrical Engineering will be prepared for future employment in the area of applied research and in technology research teams. Due to the comprehensive use of computer engineering throughout the study programme, the graduates will be well prepared for work in the area of scientific and technology software development and maintenance. The graduates will also be prepared for management and analytical positions in companies requiring good knowledge of mathematical modelling, statistics and optimization.

Applied algebraic and topological methods in analysis of continuous and dicrete processes

The dissertation will be focused on study and development of methods comming out from algebraic and topological properties of the fundamental mathematical structures and the structures of applied mathematics. The most intention will be devoted especially to certain context, causal and generalized metric structures. The results will be used for the analysis of continuous as well as discrete processes with possible applications in computer science, cybernetics, physics and biomedicine.

The aim of the dissertation thesis is modification of the differential transformation method and iteration method with difference kernel to solving initial and boundary value problems for partial differential equations. Convergence analysis of mentioned methods will be investigated as well.

Stochastic differential equations and their applications to
electrical network

By adding some randomness to the coefficients of an ordinary
differential equation we get stochastic differential equations.
Such an equation describes the current in an RL circuit with
stochastic source. Then the solution of the equation is a random
process. The subject involves creating stochastic models,
numerical solutions of stochastic differential equations and examinations of the statistical estimates of the solutions.

Fuzzy logic is a form of many-valued logic or probabilistic logic. It
has been applied to many fields, from control theory to artificial
intelligence. Modeling of real situations requires fuzzy logic
connectives.
The modelling of fuzzy logic connectives is often realized via uninorms.